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PRECOND07 au Cerfacs

2007 International Conference On Preconditioning Techniques For Large Sparse Matrix Problems In Scientific And Industrial Applications

July 9-12, 2007
Météopole, Toulouse, France


Jointly organized by CERFACS and ENSEEIHT (N7)-IRIT


Adobe_PDF_file_icon_24x24  Proceedings

CEA , CERFACS , EADS , ENSEEIHT-IRIT , INRIA , Région Midi-Pyrénées , The Boeing Company , Total , UPS


In cooperation with
Société de Mathématiques Appliquées et Industrielles / Groupe pour l’Avancement des Méthodes Numériques de l’Ingénieur
Society for Industrial and Applied Mathematics / Activity Group on Linear Algebra


Conference Chairs
Esmond G. Ng, Lawrence Berkeley National Laboratory
Yousef Saad, The University of Minnesota
Wei-Pai Tang, The Boeing Company


Click here for the program


The 2007 International Conference on Preconditioning Techniques for Large Sparse Matrix Problems in Scientific and Industrial Applications, Preconditioning 2007, is the fifth in a series of conferences that focus on preconditioning techniques in sparse matrix computation.  Past Preconditioning Conferences were :

Preconditioning 1999, The University of Minnesota, Minneapolis, June 10-12 1999.
Preconditioning 2001, The Granlibakken Conference Center, Tahoe City, April 29 – May 1, 2001.
Preconditioning 2003, Embassy Suites Napa Valley, Napa, October 27-29, 2003.
Preconditioning 2005, Emory University, Atlanta, May 19-21, 2005.

The goal of this series of conferences is to address the complex issues related to the solution of general sparse matrix problems in large-scale real applications and in industrial settings.  The issues related to sparse matrix software that are of interest to application scientists and industrial users are often fairly different from those on which the academic community is focused.  For example, for an application scientist or an industrial user, improving robustness may be far more important than finding a method that would gain speed.  Memory usage is also an important consideration, but is seldom accounted for in academic research on sparse matrix solvers.  As a last example, linear systems solved in applications are almost always part of some nonlinear iteration (e.g., Newton) or optimization loop.  It is important to consider the coupling between the linear and nonlinear parts, instead of focusing on the linear systems alone.

The speakers of this conference will discuss some of the latest developments in the field of preconditioning techniques for sparse matrix problems.  The conference will allow participants to exchange findings in this area and to explore possible new directions in light of emerging paradigms, such as parallel processing and object-oriented programming.